Improving quantification of methane point source emissions from imaging spectroscopy

Z Pei, G Han, H Mao, C Chen, T Shi, K Yang… - Remote Sensing of …, 2023 - Elsevier
The matched filter (MF) method is widely used for hyperspectral imaging spectrometers to
detect and quantify methane point sources due to its high computational efficiency …

Automated detection and monitoring of methane super-emitters using satellite data

BJ Schuit, JD Maasakkers, P Bijl… - Atmospheric …, 2023 - acp.copernicus.org
A reduction in anthropogenic methane emissions is vital to limit near-term global warming. A
small number of so-called super-emitters is responsible for a disproportionally large fraction …

Semantic segmentation of methane plumes with hyperspectral machine learning models

V Růžička, G Mateo-Garcia, L Gómez-Chova… - Scientific Reports, 2023 - nature.com
Methane is the second most important greenhouse gas contributor to climate change; at the
same time its reduction has been denoted as one of the fastest pathways to preventing …

STARCOP: Semantic Segmentation of Methane Plumes with Hyperspectral Machine Learning Models

V Růžička, G Mateo-Garcia, L Gómez-Chova… - 2023 - researchsquare.com
Methane is the second most important greenhouse gas contributor to climate change; at the
same time its reduction has been denoted as one of the fastest pathways to preventing …

Separating and Quantifying Facility-Level Methane Emissions with Overlap** Plumes for Spaceborne Methane Monitoring

Y Pang, L Tian, D Hu, S Gao, G Liu - EGUsphere, 2023 - egusphere.copernicus.org
Quantifying facility-level methane emission rates using satellites with fine spatial resolution
has recently gained significant attention. However, the existing quantification algorithms …